Location
https://www.kennesaw.edu/ccse/events/computing-showcase/fa24-cday-program.php
Event Website
https://github.com/nverma42/Chatbot
Document Type
Event
Start Date
19-11-2024 4:00 PM
Description
Mental health support is crucial, but access to professional care can be limited by cost, availability, and social stigma. Digital solutions, particularly chatbots, offer an accessible and scalable approach to providing mental health support. However, current chatbot solutions may not always reflect the diversity of users' emotional experiences, and they may lack the specialized domain knowledge and adaptability required for effective mental health counseling. This research project aims to address these challenges by developing a compassionate AI digital assistant that can use specialized natural language processing (NLP) models to provide empathetic and targeted responses based on the nature of the user's query. Unlike traditional chatbots that rely on fine-tuning large language models, our approach is to build conversation graphs for specific mental health scenarios, which can maintain historical context and adapt in real-time to the user's emotional state. The motivation for this project stems from the growing mental health crisis and the projected shortage of mental health professionals in the coming years. As advancements in digital technology and the industrial economy have contributed to increased mental health challenges, the demand for mental health care is expected to grow significantly, outpacing the available workforce. By creating a digital assistant capable of providing emotional support and evidence-based guidance, this research aims to help fill the anticipated gap in mental health services and improve access to mental health resources for those in need.
Included in
GPR-151 Compassionate Digital Assistant: Anchor
https://www.kennesaw.edu/ccse/events/computing-showcase/fa24-cday-program.php
Mental health support is crucial, but access to professional care can be limited by cost, availability, and social stigma. Digital solutions, particularly chatbots, offer an accessible and scalable approach to providing mental health support. However, current chatbot solutions may not always reflect the diversity of users' emotional experiences, and they may lack the specialized domain knowledge and adaptability required for effective mental health counseling. This research project aims to address these challenges by developing a compassionate AI digital assistant that can use specialized natural language processing (NLP) models to provide empathetic and targeted responses based on the nature of the user's query. Unlike traditional chatbots that rely on fine-tuning large language models, our approach is to build conversation graphs for specific mental health scenarios, which can maintain historical context and adapt in real-time to the user's emotional state. The motivation for this project stems from the growing mental health crisis and the projected shortage of mental health professionals in the coming years. As advancements in digital technology and the industrial economy have contributed to increased mental health challenges, the demand for mental health care is expected to grow significantly, outpacing the available workforce. By creating a digital assistant capable of providing emotional support and evidence-based guidance, this research aims to help fill the anticipated gap in mental health services and improve access to mental health resources for those in need.
https://digitalcommons.kennesaw.edu/cday/Fall_2024/PhD_Research/5